Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Uses of Class
de.lmu.ifi.dbs.elki.distance.DoubleDistance

Packages that use DoubleDistance
de.lmu.ifi.dbs.elki.algorithm Algorithms suitable as a task for the KDDTask main routine. 
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation Correlation clustering algorithms 
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces. 
de.lmu.ifi.dbs.elki.algorithm.outlier Outlier detection algorithms 
de.lmu.ifi.dbs.elki.database ELKI database layer - loading, storing, indexing and accessing data 
de.lmu.ifi.dbs.elki.distance Distances and (in subpackages) distance functions and similarity functions
de.lmu.ifi.dbs.elki.distance.distancefunction Distance functions for use within ELKI. 
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter Distance functions deriving distances from e.g. similarity measures 
de.lmu.ifi.dbs.elki.distance.distancefunction.external Distance functions using external data sources. 
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace Distance functions based on subspaces. 
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries Distance functions designed for time series. 
de.lmu.ifi.dbs.elki.distance.similarityfunction Similarity functions. 
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel Kernel functions. 
de.lmu.ifi.dbs.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and Eigenvector processing. 
de.lmu.ifi.dbs.elki.preprocessing Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures. 
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm
 

Fields in de.lmu.ifi.dbs.elki.algorithm with type parameters of type DoubleDistance
private  PCAFilteredRunner<V,DoubleDistance> DependencyDerivator.pca
          Holds the object performing the pca.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
 

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation declared as DoubleDistance
(package private)  DoubleDistance ORCLUS.ProjectedEnergy.projectedEnergy
           
 

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type parameters of type DoubleDistance
private  PCARunner<V,DoubleDistance> ORCLUS.pca
          The PCA utility object.
 

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type DoubleDistance
ORCLUS.ProjectedEnergy(int i, int j, ORCLUS.ORCLUSCluster cluster, DoubleDistance projectedEnergy)
           
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
 

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type DoubleDistance
private  Map<Integer,List<DistanceResultPair<DoubleDistance>>> PROCLUS.getLocalities(Set<Integer> m_c, Database<V> database)
          Computes the localities of the specified medoids.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.outlier
 

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type DoubleDistance
private  ClassParameter<KernelFunction<V,DoubleDistance>> ABOD.KERNEL_FUNCTION_PARAM
          Parameter for Kernel function.
(package private)  KernelFunction<V,DoubleDistance> ABOD.kernelFunction
          Store the configured Kernel version
 

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier that return types with arguments of type DoubleDistance
private  KNNList<DoubleDistance> SOD.getKNN(Database<V> database, Integer queryObject)
          Provides the k nearest neighbors in terms of the shared nearest neighbor distance.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.database
 

Fields in de.lmu.ifi.dbs.elki.database with type parameters of type DoubleDistance
static AssociationID<DoubleDistance> AssociationID.DOUBLE_DISTANCE
          The association id to associate a DoubleDistance to an object.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance
 

Methods in de.lmu.ifi.dbs.elki.distance that return DoubleDistance
 DoubleDistance DoubleDistance.minus(DoubleDistance distance)
           
 DoubleDistance DoubleDistance.plus(DoubleDistance distance)
           
 DoubleDistance DoubleDistance.times(double lambda)
          Returns a new distance as the product of this distance and the given double value.
 DoubleDistance DoubleDistance.times(DoubleDistance distance)
          Returns a new distance as the product of this distance and the given distance.
 

Methods in de.lmu.ifi.dbs.elki.distance with parameters of type DoubleDistance
 DoubleDistance DoubleDistance.minus(DoubleDistance distance)
           
 DoubleDistance DoubleDistance.plus(DoubleDistance distance)
           
 DoubleDistance DoubleDistance.times(DoubleDistance distance)
          Returns a new distance as the product of this distance and the given distance.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction
 

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type DoubleDistance
(package private)  ClassParameter<KernelFunction<V,DoubleDistance>> KernelBasedLocallyWeightedDistanceFunction.KERNEL_FUNCTION_PARAM
          Parameter for the kernel function
private  KernelFunction<V,DoubleDistance> KernelBasedLocallyWeightedDistanceFunction.kernelFunction
          The kernel function that is used.
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return DoubleDistance
 DoubleDistance LocallyWeightedDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance EuclideanDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance LocallyWeightedDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance EuclideanDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance LPNormDistanceFunction.distance(V v1, V v2)
          Returns the distance between the specified FeatureVectors as a LP-Norm for the currently set p.
 DoubleDistance KernelBasedLocallyWeightedDistanceFunction.distance(V v1, V v2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 DoubleDistance WeightedDistanceFunction.distance(V o1, V o2)
          Provides the Weighted distance for feature vectors.
 DoubleDistance CosineDistanceFunction.distance(V v1, V v2)
          Computes the cosine distance for two given feature vectors.
 DoubleDistance ManhattanDistanceFunction.distance(V v1, V v2)
           
 DoubleDistance LocallyWeightedDistanceFunction.distance(V v1, V v2)
          Computes the distance between two given real vectors according to this distance function.
 DoubleDistance ArcCosineDistanceFunction.distance(V v1, V v2)
          Computes the cosine distance for two given feature vectors.
 DoubleDistance EuclideanDistanceFunction.distance(V v1, V v2)
          Provides the Euclidean distance between the given two vectors.
 DoubleDistance AbstractDoubleDistanceFunction.infiniteDistance()
          An infinite DoubleDistance is based on Double.POSITIVE_INFINITY.
 DoubleDistance LocallyWeightedDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
           
 DoubleDistance EuclideanDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
           
 DoubleDistance LocallyWeightedDistanceFunction.minDist(HyperBoundingBox mbr, V v)
           
 DoubleDistance EuclideanDistanceFunction.minDist(HyperBoundingBox mbr, V v)
           
 DoubleDistance AbstractDoubleDistanceFunction.nullDistance()
          A null DoubleDistance is based on 0.
 DoubleDistance AbstractDoubleDistanceFunction.undefinedDistance()
          An undefined DoubleDistance is based on Double.NaN.
 DoubleDistance AbstractDoubleDistanceFunction.valueOf(String pattern)
          As pattern is required a String defining a Double.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter
 

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter with type parameters of type DoubleDistance
protected  ClassParameter<NormalizedSimilarityFunction<V,DoubleDistance>> SimilarityAdapterAbstract.SIMILARITY_FUNCTION_PARAM
          Parameter to specify the similarity function to derive the distance between database objects from.
protected  NormalizedSimilarityFunction<V,DoubleDistance> SimilarityAdapterAbstract.similarityFunction
          Holds the similarity function.
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter that return DoubleDistance
abstract  DoubleDistance SimilarityAdapterAbstract.distance(V v1, V v2)
          Distance implementation
 DoubleDistance SimilarityAdapterArccos.distance(V v1, V v2)
          Distance implementation
 DoubleDistance SimilarityAdapterLinear.distance(V v1, V v2)
          Distance implementation
 DoubleDistance SimilarityAdapterLn.distance(V v1, V v2)
          Distance implementation
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.external
 

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type parameters of type DoubleDistance
private  Map<Pair<Integer,Integer>,DoubleDistance> FileBasedDoubleDistanceFunction.cache
           
private  DistanceParser<V,DoubleDistance> FileBasedDoubleDistanceFunction.parser
           
private  ClassParameter<DistanceParser<V,DoubleDistance>> FileBasedDoubleDistanceFunction.PARSER_PARAM
          Optional parameter to specify the parsers to provide a database, must extend DistanceParser.
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.external that return DoubleDistance
 DoubleDistance DiskCacheBasedDoubleDistanceFunction.distance(Integer id1, Integer id2)
          Returns the distance between the two objects specified by their objects ids.
 DoubleDistance FileBasedDoubleDistanceFunction.distance(Integer id1, Integer id2)
          Returns the distance between the two objects specified by their objects ids.
 DoubleDistance DiskCacheBasedDoubleDistanceFunction.distance(Integer id1, V o2)
          Returns the distance between the two specified objects.
 DoubleDistance FileBasedDoubleDistanceFunction.distance(Integer id1, V o2)
          Returns the distance between the two specified objects.
 DoubleDistance DiskCacheBasedDoubleDistanceFunction.distance(V o1, V o2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 DoubleDistance FileBasedDoubleDistanceFunction.distance(V o1, V o2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that return DoubleDistance
 DoubleDistance DimensionsSelectingEuclideanDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance DimensionSelectingDistanceFunction.centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance DimensionsSelectingEuclideanDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance DimensionSelectingDistanceFunction.distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2)
           
 DoubleDistance DimensionsSelectingEuclideanDistanceFunction.distance(V v1, V v2)
          Provides the Euclidean distance between two given feature vectors in the selected dimensions.
 DoubleDistance DimensionSelectingDistanceFunction.distance(V v1, V v2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 DoubleDistance DimensionsSelectingEuclideanDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
           
 DoubleDistance DimensionSelectingDistanceFunction.minDist(HyperBoundingBox mbr, Integer id)
           
 DoubleDistance DimensionsSelectingEuclideanDistanceFunction.minDist(HyperBoundingBox mbr, V v)
           
 DoubleDistance DimensionSelectingDistanceFunction.minDist(HyperBoundingBox mbr, V v)
           
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries that return DoubleDistance
 DoubleDistance LCSSDistanceFunction.distance(V v1, V v2)
          Provides the Longest Common Subsequence distance between the given two vectors.
 DoubleDistance ERPDistanceFunction.distance(V v1, V v2)
          Provides the Edit Distance With Real Penalty distance between the given two vectors.
 DoubleDistance DTWDistanceFunction.distance(V v1, V v2)
          Provides the Dynamic Time Warping distance between the given two vectors.
 DoubleDistance EDRDistanceFunction.distance(V v1, V v2)
          Provides the Edit Distance on Real Sequence distance between the given two vectors.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction
 

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction that return DoubleDistance
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.infiniteDistance()
           
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.nullDistance()
           
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.similarity(Integer id1, Integer id2)
           
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.similarity(O o1, O o2)
           
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.undefinedDistance()
           
 DoubleDistance FractionalSharedNearestNeighborSimilarityFunction.valueOf(String pattern)
           
 

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction with parameters of type DoubleDistance
 boolean FractionalSharedNearestNeighborSimilarityFunction.isInfiniteDistance(DoubleDistance distance)
           
 boolean FractionalSharedNearestNeighborSimilarityFunction.isNullDistance(DoubleDistance distance)
           
 boolean FractionalSharedNearestNeighborSimilarityFunction.isUndefinedDistance(DoubleDistance distance)
           
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel
 

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that return DoubleDistance
 DoubleDistance ArbitraryKernelFunctionWrapper.distance(Integer id1, Integer id2)
          Returns the distance between the two objects specified by their object ids.
 DoubleDistance AbstractDoubleKernelFunction.distance(O fv1, O fv2)
           
 DoubleDistance ArbitraryKernelFunctionWrapper.distance(O o1, O o2)
          Returns the distance between the two specified objects.
 DoubleDistance AbstractDoubleKernelFunction.infiniteDistance()
          An infinite DoubleDistance is based on Double.POSITIVE_INFINITY.
 DoubleDistance AbstractDoubleKernelFunction.nullDistance()
          A null DoubleDistance is based on 0.
 DoubleDistance FooKernelFunction.similarity(O o1, O o2)
          Provides an experimental kernel similarity between the given two vectors.
 DoubleDistance LinearKernelFunction.similarity(O o1, O o2)
          Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2
 DoubleDistance ArbitraryKernelFunctionWrapper.similarity(O o1, O o2)
          Provides a wrapper for arbitrary kernel functions whose kernel matrix has already been precomputed.
 DoubleDistance PolynomialKernelFunction.similarity(O o1, O o2)
          Provides the linear kernel similarity between the given two vectors.
 DoubleDistance AbstractDoubleKernelFunction.undefinedDistance()
          An undefined DoubleDistance is based on Double.NaN.
 DoubleDistance AbstractDoubleKernelFunction.valueOf(String pattern)
          As pattern is required a String defining a Double.
 

Constructor parameters in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with type arguments of type DoubleDistance
KernelMatrix(KernelFunction<O,DoubleDistance> kernelFunction, Database<O> database)
          Provides a new kernel matrix.
KernelMatrix(KernelFunction<O,DoubleDistance> kernelFunction, Database<O> database, List<Integer> ids)
          Provides a new kernel matrix.
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
 

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type parameters of type DoubleDistance
private  DistanceFunction<V,DoubleDistance> WeightedCovarianceMatrixBuilder.weightDistance
          Holds the distance function used for weight calculation
 

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.preprocessing
 

Fields in de.lmu.ifi.dbs.elki.preprocessing declared as DoubleDistance
static DoubleDistance DiSHPreprocessor.DEFAULT_EPSILON
          The default value for epsilon.
private  DoubleDistance[] DiSHPreprocessor.epsilon
          The epsilon value for each dimension;
 

Fields in de.lmu.ifi.dbs.elki.preprocessing with type parameters of type DoubleDistance
private  PCAFilteredRunner<V,DoubleDistance> HiCOPreprocessor.pca
          PCA utility object
protected  ClassParameter<DistanceFunction<V,DoubleDistance>> HiCOPreprocessor.PCA_DISTANCE_PARAM
          Parameter to specify the distance function used for running PCA.
protected  DistanceFunction<V,DoubleDistance> HiCOPreprocessor.pcaDistanceFunction
          The distance function for the PCA.
 

Methods in de.lmu.ifi.dbs.elki.preprocessing that return DoubleDistance
 DoubleDistance[] DiSHPreprocessor.getEpsilon()
          Returns the value of the epsilon parameter.
 

Methods in de.lmu.ifi.dbs.elki.preprocessing that return types with arguments of type DoubleDistance
protected  List<DistanceResultPair<DoubleDistance>> KnnQueryBasedHiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
           
protected  List<DistanceResultPair<DoubleDistance>> RangeQueryBasedHiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
           
protected abstract  List<DistanceResultPair<DoubleDistance>> HiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
          Returns the ids of the objects and distances stored in the specified database to be considered within the PCA for the specified object id.
 


Release 0.2 (2009-07-06_1820)